The Impact of Liquidity on Option Prices. Robin K. Chou Department of Finance, National Chengchi University San-Lin Chung and Yaw-Huei Wang Department of Finance, National Taiwan University Yu-Jen Hsiao Department of Finance, National Central University. Introduction.

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liquidity factors are important determinants of stock and bond returns

returns have been found to be affected by liquidity, as measured by the bid-ask spread (Amihud and Mendelson, 1986a, 1991), the price impact of trades (Brennan and Subrahmanyam, 1996), and volume or turnover ratio (Datar, Naik, and Radcliffe, 1998).

Options with a lower proportional bid-ask spread have a higher level of model-free implied volatility. This finding is consistent with the ‘illiquidity premium’ hypothesis proposed by Amihud and Mendelson (1986a)

Options become more expensive when the spot asset is less liquid, which is consistent with the findings of Cetin et al. (2006)

The liquidity of options can partly explain the implied volatility ‘smile’ documented by Rubinstein (1985) and others. When the option market becomes more liquid (i.e. when there is a lower option proportional bid-ask spread), the implied volatility curve becomes steeper (more negatively skewed).

We next test the effect of the most significant liquidity proxies on MFIV of options simultaneously. The results are reported in Table 5.

Three most significant spot liquidity proxy variables (VOL, ATS, and AQS) and the three most significant option liquidity measures (DVOL, OAQS, and OI) are simultaneously included into a regression model with the six control variables.

Among all of the spot liquidity proxies, the average of the AQS coefficients is still found to be highly and positively significant, whereas the averages of the VOL and ATS coefficients are not significant.

For the option liquidity measures, the coefficient averages of all option liquidity proxies are significant at below the 1 per cent level. Moreover, the cross-sectional proportion of OAQS with significance is found to be the highest, at 70 per cent.

The findings of Tables 4 and 5 imply that low spot liquidity leads to high option prices, with options becoming less expensive when the options market becomes more illiquid; this is consistent with the hedging cost explanation provided by Cetin et al. (2006) and the ‘illiquidity premium’ hypothesis of Amihud and Mendelson (1986a).

To mitigates the concern that our results may depend on the time to maturity of options, we also compile all of the option-related data for the 60-, 91-, and 182-day maturity periods, and then rerun all of the tests in Table 5. The results are reported in Table 6.

Our empirical findings are robust across maturity periods with AQS and OAQS being found to be the most robust liquidity measures.

We perform the following month-by-month cross-sectional regression to test Hypotheses 1a and 1b.

The results reported in Panel A of Table 7 confirm those of Duan and Wei (2009), who note that after controlling for stock-specific total volatility, the implied volatility level is significantly and positively related to the systematic risk proportion of the underlying stock.

Panel B of Table 7 reveals strong evidence for the rejection of Hypotheses 1a and 1b, with the effect of spot and option liquidity on the implied volatility level remaining significant at the 1 per cent level, even after controlling for the influence of risk-neutral skewness, kurtosis, and the systematic risk proportion.

We also perform the following month-by-month cross-sectional regression to test Hypotheses 2a and 2b.

Panel A of Table 8 supports the findings of Duan and Wei (2009) that the slope of the implied volatility curve is related to the systematic risk proportion, although not all of the coefficients are found to be statistically significant.